Temporal-Mapping Photography for Event Cameras

• URL: http://arxiv.org/abs/2403.06443v2
• Date: Tue, 12 Nov 2024 06:11:46 GMT
• Title: Temporal-Mapping Photography for Event Cameras
• Authors: Yuhan Bao, Lei Sun, Yuqin Ma, Kaiwei Wang,
• Abstract summary: Event cameras, or Dynamic Vision Sensors (DVS), capture brightness changes as a continuous stream of "events" Converting sparse events to dense intensity frames faithfully has long been an ill-posed problem. In this paper, for the first time, we realize events to dense intensity image conversion using a stationary event camera in static scenes.
• Score: 5.344756442054121
• License:
• Abstract: Event cameras, or Dynamic Vision Sensors (DVS) are novel neuromorphic sensors that capture brightness changes as a continuous stream of "events" rather than traditional intensity frames. Converting sparse events to dense intensity frames faithfully has long been an ill-posed problem. Previous methods have primarily focused on converting events to video in dynamic scenes or with a moving camera. In this paper, for the first time, we realize events to dense intensity image conversion using a stationary event camera in static scenes with a transmittance adjustment device for brightness modulation. Different from traditional methods that mainly rely on event integration, the proposed Event-Based Temporal Mapping Photography (EvTemMap) measures the time of event emitting for each pixel. Then, the resulting Temporal Matrix is converted to an intensity frame with a temporal mapping neural network. At the hardware level, the proposed EvTemMap is implemented by combining a transmittance adjustment device with a DVS, named Adjustable Transmittance Dynamic Vision Sensor (AT-DVS). Additionally, we collected TemMat dataset under various conditions including low-light and high dynamic range scenes. The experimental results showcase the high dynamic range, fine-grained details, and high-grayscale resolution of the proposed EvTemMap. The code and dataset are available in https://github.com/YuHanBaozju/EvTemMap

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